IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Utilizing AI in Learning English Vocabulary among EFL Omani Students: The Relationship of Academic Performance and English Proficiency

Utilizing AI in Learning English Vocabulary among EFL Omani Students: The Relationship of Academic Performance and English Proficiency
View Sample PDF
Author(s): Nayef J. Jomaa (University of Technology and Applied Sciences, Salalah, Oman), Salim Al Maashani (Infrastructure University Kuala Lumpur, Slangor, Malaysia)and Ahmed Almaashani (University of Bristol, Bristol, UK)
Copyright: 2025
Pages: 32
Source title: Modern Methods for AI-Integrated Language Curriculum
Source Author(s)/Editor(s): Nayef Jomaa (University of Technology and Applied Sciences, Oman)
DOI: 10.4018/979-8-3693-9606-3.ch001

Purchase


Abstract

This study investigates the impact of AI-integrated vocabulary learning on EFL Omani students, focusing on their academic performance and English proficiency. A quantitative approach was employed, employing data collection through a survey distributed to 500 students, with 236 valid responses analysed. SPSS version 26 was used in the analysis. The findings revealed that EFL Omani students generally perceive AI tools as beneficial for vocabulary acquisition and learning, with higher proficiency and academically stronger students demonstrating greater trust, ease of use, and motivation to engage with AI-driven learning. However, lower-proficiency students and those with weaker academic performance reported more challenges in using AI tools and exhibited lower trust in AI-generated vocabulary recommendations. Though general trends indicate a positive correlation between proficiency level and AI learning effectiveness, statistical analyses showed no significant impact of academic performance on AI-assisted vocabulary acquisition.

Related Content

Supriadi Supriadi, Andi Asrifan. © 2026. 26 pages.
Vishal Jain, Archan Mitra, Sanchita Paul. © 2026. 20 pages.
Sooraj Kumar Maurya, Vikash Ranjan Singh. © 2026. 24 pages.
Mustafa Kayyali. © 2026. 26 pages.
Muhammad Rapi. © 2026. 26 pages.
Andi Sukri Syamsuri, Andi Asrifan. © 2026. 26 pages.
Siti Hajar Larekeng. © 2026. 28 pages.
Body Bottom